Integrated Multiomic Profiling Enhances Risk Stratification and Prognostication in Canine Osteosarcoma

Osteosarcoma is a heterogeneous and aggressive primary bone malignancy that affects both canines and humans. Standardized treatment regimens prescribed to both species do not address the complexity of the disease and thus have resulted in stagnant patient outcomes for more than 30 years.

In this study, we present the first multiomic dataset created from a large outcome-linked biobank of canine osteosarcoma treatment-naïve primary tumors, utilizing a computational framework designed to interrogate each dataset individually and to compare and integrate findings.

This exploratory work suggests that the presence of MYC amplification is a poor prognostic indicator in canines and highlights alterations in DNA damage repair, metabolism, and cell-cycle genes that are shared with humans. Furthermore, we show relationships between the local tumor immune microenvironment, TP53 mutations, MYC and PTEN status, and global gene methylation patterns.

This work highlights the complexity of the disease and provides new insight into the utility of prognostic biomarkers and potential druggable targets for future study.